Mathematics teaching quality evaluation research based on harmony search BP neural network
COMPUTER MODELLING & NEW TECHNOLOGIES 2014 18(12C) 1315-1319
College of Mathematics and Information Science, Xianyang Normal University, Xianyang, Shaanxi China, 712000
The focus of improving the quality of mathematics education is to improve the quality of teaching, so that teaching evaluation is the key to improve the teaching quality of education. BP algorithm is used to evaluate mathematics teaching quality, but it is easy to fall into local optimum and has low convergence speed. Harmony search is used to optimize weight and threshold of BP neural network. Then mathematics teaching quality evaluation based on improved BP neural network is proposed. The experiment results show that the improved BP neural network has faster convergence speed and is more precise than traditional BP neural network. It can evaluate teaching quality more scientifically and accurately.